function F = cal_model_moment(param, const, eqm)

    % Read-in
    sigma           = param.sigma;
%     beta_v          = param.beta_v;
%     beta_m          = param.beta_m;    
    d               = param.d;
    Q               = param.Q;    
    gamma           = 1;
%     phi_v           = const.phi_v;
    phi_y           = const.phi_y;
    lnzQ            = const.lnzQ;        
    density_omega   = const.density_omega;    
%     C_v0            = const.C_v0; 
%     C_m             = const.C_m;    
    lnwage_grid     = const.lnwage_grid;  
    q_indicator     = eqm.q_indicator;
    nq              = eqm.nq;
    nd              = eqm.nd;
    quintileflag    = eqm.quintileflag;   
    E_zx0           = eqm.integ.E_zx0;
    E_zx1           = eqm.integ.E_zx1;
%     E_zv0           = eqm.integ.E_zv0;
%     E_zv1           = eqm.integ.E_zv1;  
%     E_zm0           = eqm.integ.E_zm0;        
%     E_zm1           = eqm.integ.E_zm1;           
    ExportProbQ     = eqm.ExportProbQ;   
%     C_v1            = eqm.C_v1;    
    Pi0             = eqm.Pi0;
    Pi1             = eqm.Pi1;
%     V               = eqm.V;
%     M               = eqm.M;
%     theta_v         = eqm.theta_v;
%     theta_m         = eqm.theta_m; 
    X_m             = eqm.X_m;
    Psig            = eqm.Psig;
    c               = eqm.c;    
%     rv_ads          = eqm.rv_ads;
    rv_rev          = 1-eqm.D_F./eqm.D1;   
    
    
    
%% Model Moments: Exporter Share and Export Intensity

    % Fraction of exporters 
    exporter_share_q = density_omega'*(ExportProbQ.*q_indicator)./nq;
    exporter_share_q(nq==0)=0;
    exporter_share_d = (sum(repmat(exporter_share_q.*nq,d,1).*quintileflag,2)./sum(repmat(nq,d,1).*quintileflag,2))';
    exporter_share = sum(exporter_share_q.*nq);  
        
    % Export intensity of exporters
    export_intensity_q = 1-rv_rev;
    export_intensity_d = (sum(repmat((1-rv_rev).*exporter_share_q.*nq,d,1).*quintileflag,2)./sum(repmat(exporter_share_q.*nq,d,1).*quintileflag,2))';
    export_intensity = sum((1-rv_rev).*nq);
    
    % Useful notation
    nq_exp = nq.*exporter_share_q;
    nq_nonexp = nq.*(1-exporter_share_q);
    
    % Store
    model.exporter_share_q      = exporter_share_q;
    model.exporter_share_d      = exporter_share_d;
    model.exporter_share        = exporter_share;
    model.export_intensity_q    = export_intensity_q;
    model.export_intensity_d    = export_intensity_d;
    model.export_intensity      = export_intensity;
    
    
    
%% Model Moments: Mean In-degree and Out-degree
    

    model.mean_indegree_d = ones(1,d)*eqm.newmbar;
    model.mean_outdegree_d = ones(1,d)*eqm.newmbar;

 
%     % Useful notation
%     Vbar = C_v0.*Pi0.^(1/beta_v).*E_zv0 + rv_ads.*C_v1.*Pi1.^(1/beta_v).*E_zv1;
%         
%     % Mean in-degree by q
%     mean_indegree_q = M.*theta_m./nq;
%     mean_indegree_q_exp = theta_m./nq_exp.*C_m.*Pi1.^(1/beta_m).*E_zm1;
%     mean_indegree_q_nonexp = theta_m./nq_nonexp.*C_m.*Pi0.^(1/beta_m).*E_zm0;
%     
%     % Mean out-degree by q
%     mean_outdegree_q = Vbar.*sum(phi_v.*repmat(theta_v',1,Q),1)./nq;   
%     mean_outdegree_q_exp = rv_ads.*C_v1.*Pi1.^(1/beta_v).*E_zv1.*sum(phi_v.*repmat(theta_v',1,Q),1)./nq_exp;
%     mean_outdegree_q_nonexp = C_v0.*Pi0.^(1/beta_v).*E_zv0.*sum(phi_v.*repmat(theta_v',1,Q),1)./nq_nonexp;
%     
%         % Adjustment
%         mean_indegree_q(nq==0)=0;    
%         mean_indegree_q_exp(nq==0)=0;    
%         mean_indegree_q_nonexp(nq==0)=0;   
%         mean_outdegree_q(nq==0)=0;     
%         mean_outdegree_q_exp(nq==0)=0;   
%         mean_outdegree_q_nonexp(nq==0)=0;
% 
%         % Check
%         %check1 = mean(abs(mean_indegree_q_nonexp.*nq_nonexp + mean_indegree_q_exp.*nq_exp - mean_indegree_q.*nq));
%         %check2 = mean(abs(mean_outdegree_q_nonexp.*nq_nonexp + mean_outdegree_q_exp.*nq_exp - mean_outdegree_q.*nq));
% 
%     % Mean in-degree by quintile
%     mean_indegree_d =  (sum(repmat(mean_indegree_q.*nq,d,1).*quintileflag,2)./sum(repmat(nq,d,1).*quintileflag,2))';
%     mean_indegree_d_exp = (sum(repmat(mean_indegree_q_exp.*nq_exp,d,1).*quintileflag,2)./sum(repmat(nq_exp,d,1).*quintileflag,2))';
%     mean_indegree_d_nonexp = (sum(repmat(mean_indegree_q_nonexp.*nq_nonexp,d,1).*quintileflag,2)./sum(repmat(nq_nonexp,d,1).*quintileflag,2))';
%     
%     % Mean out-degrees by quintile
%     mean_outdegree_d =(sum(repmat(mean_outdegree_q.*nq,d,1).*quintileflag,2)./sum(repmat(nq,d,1).*quintileflag,2))';  
%     mean_outdegree_d_exp = (sum(repmat(mean_outdegree_q_exp.*nq_exp,d,1).*quintileflag,2)./sum(repmat(nq_exp,d,1).*quintileflag,2))';  
%     mean_outdegree_d_nonexp = (sum(repmat(mean_outdegree_q_nonexp.*nq_nonexp,d,1).*quintileflag,2)./sum(repmat(nq_nonexp,d,1).*quintileflag,2))';  
%          
%     % Mean in-degrees for all
%     mean_indegree = sum(mean_indegree_q.*nq);
%     mean_indegree_exp = sum(mean_indegree_q_exp.*nq_exp)./sum(nq_exp);
%     mean_indegree_nonexp = sum(mean_indegree_q_nonexp.*nq_nonexp)./sum(nq_nonexp);
%    
%     % Mean out-degree for all
%     mean_outdegree = sum(mean_outdegree_q.*nq);
%     mean_outdegree_exporter = sum(mean_outdegree_q_exp.*nq_exp)./sum(nq_exp);
%     mean_outdegree_nonexp = sum(mean_outdegree_q_nonexp.*nq_nonexp)./sum(nq_nonexp);
%        
%     % Store
%     model.mean_indegree_q           = mean_indegree_q;
%     model.mean_indegree_q_exp       = mean_indegree_q_exp;
%     model.mean_indegree_q_nonexp    = mean_indegree_q_nonexp;
%     model.mean_indegree_d           = mean_indegree_d;
%     model.mean_indegree_d_exp       = mean_indegree_d_exp;
%     model.mean_indegree_d_nonexp    = mean_indegree_d_nonexp;     
%     model.mean_indegree             = mean_indegree;  
%     model.mean_indegree_exp         = mean_indegree_exp;
%     model.mean_indegree_nonexp      = mean_indegree_nonexp;    
%     model.mean_outdegree_q          = mean_outdegree_q;
%     model.mean_outdegree_q_exp      = mean_outdegree_q_exp;
%     model.mean_outdegree_q_nonexp   = mean_outdegree_q_nonexp;
%     model.mean_outdegree_d          = mean_outdegree_d;
%     model.mean_outdegree_d_exp      = mean_outdegree_d_exp;  
%     model.mean_outdegree_d_nonexp   = mean_outdegree_d_nonexp;
%     model.mean_outdegree            = mean_outdegree;
%     model.mean_outdegree_exp        = mean_outdegree_exporter;
%     model.mean_outdegere_nonexp     = mean_outdegree_nonexp;
%     

%% Model Moments: Mean and Variance of Sales

    % Useful moments
    E_lnz0 = density_omega'*(lnzQ.*(1-ExportProbQ).*q_indicator)./nq;
    E_lnz1 = density_omega'*(lnzQ.*ExportProbQ.*q_indicator)./nq;
    E2_lnz0 = density_omega'*(lnzQ.^2.*(1-ExportProbQ).*q_indicator)./nq;
    E2_lnz1 = density_omega'*(lnzQ.^2.*ExportProbQ.*q_indicator)./nq;
    
        % Adjustment
        E_lnz0(nq==0)=0;
        E_lnz1(nq==0)=0;
        E2_lnz0(nq==0)=0;
        E2_lnz1(nq==0)=0;    
        
    % Mean of log sales by q
    mean_lnsales_q = (sigma-1)*gamma*E_lnz0 + log(Pi0).*(1-exporter_share_q)...
                   + (sigma-1)*gamma*E_lnz1 + log(Pi1).*exporter_share_q;                        
    mean_lnsales_q_exp = (sigma-1)*gamma*E_lnz1.*nq./nq_exp + log(Pi1);
    mean_lnsales_q_nonexp = (sigma-1)*gamma*E_lnz0.*nq./nq_nonexp + log(Pi0);          
      
        % Adjustment
        mean_lnsales_q(nq==0)=0;
        mean_lnsales_q_exp(nq==0)=0;
        mean_lnsales_q_nonexp(nq==0)=0;    
    
    % Mean of log sales by quintile           
    mean_lnsales_d = (sum(repmat(mean_lnsales_q.*nq,d,1).*quintileflag,2)./sum(repmat(nq,d,1).*quintileflag,2))';
    mean_lnsales_d_exp = (sum(repmat(mean_lnsales_q_exp.*nq_exp,d,1).*quintileflag,2)./sum(repmat(nq_exp,d,1).*quintileflag,2))';
    mean_lnsales_d_nonexp = (sum(repmat(mean_lnsales_q_nonexp.*nq_nonexp,d,1).*quintileflag,2)./sum(repmat(nq_nonexp,d,1).*quintileflag,2))';
    
    % Mean of log sales
    mean_lnsales = sum(mean_lnsales_q.*nq);
    mean_lnsales_exp = sum(mean_lnsales_q_exp.*nq_exp)./sum(nq_exp);
    mean_lnsales_nonexp = sum(mean_lnsales_q_nonexp.*nq_nonexp)./sum(nq_nonexp);
    
    % Variance of log sales by q
    var_lnsales_q = ((sigma-1)*gamma)^2*(E2_lnz0) + 2*(sigma-1)*gamma*log(Pi0).*E_lnz0 + log(Pi0).^2.*(1-exporter_share_q)...
                    +((sigma-1)*gamma)^2*(E2_lnz1) + 2*(sigma-1)*gamma*log(Pi1).*E_lnz1 + log(Pi1).^2.*exporter_share_q...
                   -(mean_lnsales_q).^2;
            
    % Variance of log sales by quintile           
    var_lnsales_d = (sum(repmat((var_lnsales_q+mean_lnsales_q.^2).*nq,d,1).*quintileflag,2)./sum(repmat(nq,d,1).*quintileflag,2))'-mean_lnsales_d.^2;   
        
    % Variance of log sales
    var_lnsales = sum((var_lnsales_q+mean_lnsales_q.^2).*nq)-mean_lnsales.^2; 
    
    
    % Store
    model.mean_lnsales_q = mean_lnsales_q;
    model.mean_lnsales_q_exp = mean_lnsales_q_exp;
    model.mean_lnsales_q_nonexp = mean_lnsales_q_nonexp;
    model.mean_lnsales_d = mean_lnsales_d;
    model.mean_lnsales_d_exp = mean_lnsales_d_exp;
    model.mean_lnsales_d_nonexp = mean_lnsales_d_nonexp;
    model.mean_lnsales = mean_lnsales;
    model.mean_lnsales_exp = mean_lnsales_exp;
    model.mean_lnsales_nonexp = mean_lnsales_nonexp;
    model.var_lnsales_q = var_lnsales_q;
    model.var_lnsales_d = var_lnsales_d;
    model.var_lnsales = var_lnsales;    
    


%% Model Moments: Network Sales Share
        
    % Mean network sales by q
    mean_network_sales_q = (Pi0.*E_zx0 + rv_rev.*Pi1.*E_zx1)./nq;
    mean_network_sales_q_exp = rv_rev.*Pi1.*E_zx1./nq_exp;
    mean_network_sales_q_nonexp = Pi0.*E_zx0./nq_nonexp; 
    
        % Adjustment
        mean_network_sales_q(nq==0)=0;
        mean_network_sales_q_exp(nq==0)=0;
        mean_network_sales_q_nonexp(nq==0)=0;
    
    % Mean network sales by quintile
    mean_network_sales_d = (sum(repmat(mean_network_sales_q.*nq,d,1).*quintileflag,2)./sum(repmat(nq,d,1).*quintileflag,2))'; 
    mean_network_sales_d_exp = (sum(repmat(mean_network_sales_q_exp.*nq_exp,d,1).*quintileflag,2)./sum(repmat(nq_exp,d,1).*quintileflag,2))'; 
    mean_network_sales_d_nonexp = (sum(repmat(mean_network_sales_q_nonexp.*nq_nonexp,d,1).*quintileflag,2)./sum(repmat(nq_nonexp,d,1).*quintileflag,2))';     

    % Network sales share by q
    network_sales_share_q = mean_network_sales_q.*nq/sum(mean_network_sales_q.*nq);
    network_sales_share_q_exp = mean_network_sales_q_exp.*nq_exp/sum(mean_network_sales_q_exp.*nq_exp);        
    network_sales_share_q_nonexp = mean_network_sales_q_nonexp.*nq_nonexp/sum(mean_network_sales_q_nonexp.*nq_nonexp);        
        
        % Adjustment
        network_sales_share_q(nq==0)=0;
        network_sales_share_q_exp(nq==0)=0;
        network_sales_share_q_nonexp(nq==0)=0; 
    
    % Network sales share by quintile
    network_sales_share_d = mean_network_sales_d.*nd/sum(mean_network_sales_d.*nd);        
    network_sales_share_d_exp = mean_network_sales_d_exp.*nd.*exporter_share_d/sum(mean_network_sales_d_exp.*nd.*exporter_share_d);        
    network_sales_share_d_nonexp = mean_network_sales_d_nonexp.*nd.*(1-exporter_share_d)/sum(mean_network_sales_d_nonexp.*nd.*(1-exporter_share_d));        
        
    % Store 
    model.network_sales_share_q         = network_sales_share_q;
    model.network_sales_share_q_exp     = network_sales_share_q_exp;
    model.network_sales_share_q_nonexp  = network_sales_share_q_nonexp;
    model.network_sales_share_d         = network_sales_share_d;    
    model.network_sales_share_d_exp     = network_sales_share_d_exp;
    model.network_sales_share_d_nonexp  = network_sales_share_d_nonexp;
        
    
    
% %% Model Moments: Aggregate Network Moments
% 
%     % Supplier and customer shares
%     common = mysum(repmat(theta_v',1,Q).*phi_v.*repmat(Vbar,Q,1), quintileflag, param);
%     share_indegree_d = common./repmat(sum(common,2),1,d);
%     share_outdegree_d = common./repmat(sum(common,1),d,1);
% 
%     % Expenditure and sales share
%     common = mysum(repmat((theta_m./V.*c.^(sigma-1).*X_m)',1,Q).*phi_y.*phi_v.*repmat(Psig,Q,1), quintileflag, param);
%     share_spend_d = common./repmat(sum(common,2),1,d);
%     share_sales_d = common./repmat(sum(common,1),d,1);
%     
%     % Store
%     model.share_indegree_d  = share_indegree_d;
%     model.share_outdegree_d = share_outdegree_d;
%     model.share_spend_d     = share_spend_d;
%     model.share_sales_d     = share_sales_d;
%     
%         
    
%% Model Moments: Average Log Wage of Suppliers

    % Average supplier wage by q (same for all/exporter/nonexporter)    
    avg_unwgt_lnwageS_q = mean(log(param.w)+lnwage_grid);
    avg_wgt_lnwageS_q = c.^(sigma-1).*sum(eqm.newmbar.*phi_y.*repmat((log(param.w)+lnwage_grid).*Psig, Q,1),2)';    

    % Average supplier wage by quintile
    avg_wgt_lnwageS_d = (sum(repmat(avg_wgt_lnwageS_q.*nq, d, 1).*quintileflag, 2)./sum(repmat(nq,d,1).*quintileflag,2))';  
    avg_wgt_lnwageS_d_exp = (sum(repmat(avg_wgt_lnwageS_q.*nq_exp, d, 1).*quintileflag, 2)./sum(repmat(nq_exp,d,1).*quintileflag,2))';  
    avg_wgt_lnwageS_d_nonexp = (sum(repmat(avg_wgt_lnwageS_q.*nq_nonexp, d, 1).*quintileflag, 2)./sum(repmat(nq_nonexp,d,1).*quintileflag,2))';  
    avg_unwgt_lnwageS_d = (sum(repmat(avg_unwgt_lnwageS_q.*nq, d, 1).*quintileflag, 2)./sum(repmat(nq,d,1).*quintileflag,2))';   
    avg_unwgt_lnwageS_d_exp = (sum(repmat(avg_unwgt_lnwageS_q.*nq_exp, d, 1).*quintileflag, 2)./sum(repmat(nq_exp,d,1).*quintileflag,2))';   
    avg_unwgt_lnwageS_d_nonexp = (sum(repmat(avg_unwgt_lnwageS_q.*nq_nonexp, d, 1).*quintileflag, 2)./sum(repmat(nq_nonexp,d,1).*quintileflag,2))';   
    
    % Average supplier wage
    avg_wgt_lnwageS = sum(avg_wgt_lnwageS_q.*nq);
    avg_wgt_lnwageS_exp = sum(avg_wgt_lnwageS_q.*nq_exp)./sum(nq_exp);
    avg_wgt_lnwageS_nonexp = sum(avg_wgt_lnwageS_q.*nq_nonexp)./sum(nq_nonexp);
    avg_unwgt_lnwageS = sum(avg_unwgt_lnwageS_q.*nq);
    avg_unwgt_lnwageS_exp = sum(avg_unwgt_lnwageS_q.*nq_exp)./sum(nq_exp);
    avg_unwgt_lnwageS_nonexp = sum(avg_unwgt_lnwageS_q.*nq_nonexp)./sum(nq_nonexp);
    
    % Store    
    model.avg_wgt_lnwageS_q           = avg_wgt_lnwageS_q;   
    model.avg_wgt_lnwageS_d           = avg_wgt_lnwageS_d;
    model.avg_wgt_lnwageS_d_exp       = avg_wgt_lnwageS_d_exp;
    model.avg_wgt_lnwageS_d_nonexp    = avg_wgt_lnwageS_d_nonexp;
    model.avg_wgt_lnwageS             = avg_wgt_lnwageS;
    model.avg_wgt_lnwageS_exp         = avg_wgt_lnwageS_exp;
    model.avg_wgt_lnwageS_nonexp      = avg_wgt_lnwageS_nonexp;   
    model.avg_unwgt_lnwageS_q         = avg_unwgt_lnwageS_q;
    model.avg_unwgt_lnwageS_d         = avg_unwgt_lnwageS_d;
    model.avg_unwgt_lnwageS_d_exp     = avg_unwgt_lnwageS_d_exp;
    model.avg_unwgt_lnwageS_d_nonexp  = avg_unwgt_lnwageS_d_nonexp;
    model.avg_unwgt_lnwageS           = avg_unwgt_lnwageS;
    model.avg_unwgt_lnwageS_exp       = avg_unwgt_lnwageS_exp; 
    model.avg_unwgt_lnwageS_nonexp    = avg_unwgt_lnwageS_nonexp;  
    model.avg_unwgt_lnwageS_d4    = model.avg_unwgt_lnwageS_d(2:5) - model.avg_unwgt_lnwageS_d(1);
    model.avg_wgt_lnwageS_d4      = model.avg_wgt_lnwageS_d(2:5) - model.avg_wgt_lnwageS_d(1);    

    
    
%% Model Moments: Wage Regression Coefficients

%     % Decompose weighted average log wage of suppliers
%     avg_wgt_lnwageS_ext_q = avg_unwgt_lnwageS_q;
%     avg_wgt_lnwageS_int_q = avg_wgt_lnwageS_q - avg_unwgt_lnwageS_q;    
%     
%     % Wage regression
%     reg_W = diag(nq);
%     reg_x = [ones(Q,1), param.w.*lnwage_grid'];
%     reg_y_ext = avg_wgt_lnwageS_ext_q';
%     reg_y_int = avg_wgt_lnwageS_int_q';
%     reg_y_sum = avg_wgt_lnwageS_q';
%     beta_ext = (reg_x'*reg_W*reg_x)\(reg_x'*reg_W*reg_y_ext);
%     beta_int = (reg_x'*reg_W*reg_x)\(reg_x'*reg_W*reg_y_int);
%     beta_sum = (reg_x'*reg_W*reg_x)\(reg_x'*reg_W*reg_y_sum);
%     slope_ext = beta_ext(2);
%     slope_int = beta_int(2);
%     slope_sum = beta_sum(2);   
% 
%     % Store    
%     model.avg_wgt_lnwageS_ext_q   = avg_wgt_lnwageS_ext_q;
%     model.avg_wgt_lnwageS_int_q   = avg_wgt_lnwageS_int_q;
%     model.slope_ext             = slope_ext;
%     model.slope_int             = slope_int;
%     model.slope_sum             = slope_sum;    
    
        
    
%% Match Quality Composition

%     % Fraction of suppliers of higher (or same) quality
%     flag_S_higher_q = zeros(param.Q, param.Q); %row is buyer, column is seller
%     for i = 1:param.Q
%         flag_S_higher_q(i,:) = [zeros(1,i-1), ones(1,param.Q-i+1)];
%     end
%     model.frac_S_higher_q = sum(flag_S_higher_q.*const.phi_v.*repmat(eqm.Vbar,param.Q,1),2)'./eqm.V;    
%     
%     
%     % Fraction of customers of higher (or same) quality
%     flag_B_higher_q = zeros(param.Q, param.Q); %row is buyer, column is seller
%     for i = 1:param.Q
%         flag_B_higher_q(:,i) = [zeros(i-1,1); ones(param.Q-i+1,1)];
%     end
%     tempmatrix = const.phi_v.*repmat(eqm.theta_v',1,param.Q);
%     model.frac_B_higher_q = sum(flag_B_higher_q.*tempmatrix,1)./sum(tempmatrix,1);        
%     
    
    
%% Number of Workers

%     % Total wage bill by q
%     model.total_wage_bill_q = (1-param.alpha_m-param.alpha_s)*(param.sigma-1)/param.sigma*(eqm.X0+eqm.X1);
%     model.total_wage_bill_q_exp = (1-param.alpha_m-param.alpha_s)*(param.sigma-1)/param.sigma*eqm.X1;
%     model.total_wage_bill_q_nonexp = (1-param.alpha_m-param.alpha_s)*(param.sigma-1)/param.sigma*eqm.X0;
%         
%     % Total number of workers by q
%     model.total_num_worker_q = model.total_wage_bill_q./const.wage_grid;
%     model.total_num_worker_q_exp = model.total_wage_bill_q_exp./const.wage_grid;
%     model.total_num_worker_q_nonexp = model.total_wage_bill_q_nonexp./const.wage_grid;
%     
%         % Adjustment
%         model.total_num_worker_q(nq==0) = 0;
%         model.total_num_worker_q_exp(nq==0) = 0;
%         model.total_num_worker_q_nonexp(nq==0) = 0;
        
           

%% Share of domestic links with at least one exporter

%     % Measure of links with at least one exporter
%     Mtilde1 = eqm.theta_v.*eqm.V1 + eqm.theta_v.*eqm.V0.*eqm.M1./eqm.M;
%     Mtilde1(eqm.nq==0) = 0;
%         % check
%         check_Mtilde1 = eqm.theta_v.*eqm.V1 + eqm.theta_m.*eqm.M1.*(1-eqm.V1./eqm.V);
%         check_zero = sum(abs(Mtilde1 - check_Mtilde1));
% 
%     % Measure of links
%     Mtilde = eqm.theta_v.*eqm.V;
% 
%     % Share of links with at least one exporter
%     model.share_dlinks_w_exporter_q = Mtilde1./Mtilde;
%     model.share_dlinks_w_exporter_q(eqm.nq==0) = 0;
%     model.share_dlinks_w_exporter_d = (sum(repmat(Mtilde1,d,1).*eqm.quintileflag,2)./sum(repmat(Mtilde,d,1).*eqm.quintileflag,2))';
%     model.share_dlinks_w_exporter = sum(Mtilde1)/sum(Mtilde);
% 

%% Share of domestic transactions with at least one exporter

%     % Non-exporter's spending share on manufacturing inputs produced by exporting suppliers
%     Share_numera = sum(const.phi_y.*const.phi_v.*repmat(eqm.P1sig,param.Q,1),2)';
%     Share_denome = sum(const.phi_y.*const.phi_v.*repmat(eqm.Psig,param.Q,1),2)';
%     Share = Share_numera./Share_denome;
% 
%     % Share of manufacturing trade in inputs involving at least one exporter
%     model.share_dtransac_w_exporter_q = (eqm.X1+eqm.X0.*Share)./(eqm.X1+eqm.X0);
%     model.share_dtransac_w_exporter_q(eqm.nq==0) = 0;
%     model.share_dtransac_w_exporter_d = (sum(repmat(eqm.X1+eqm.X0.*Share,d,1).*eqm.quintileflag,2)./sum(repmat(eqm.X1+eqm.X0,d,1).*eqm.quintileflag,2))';
%     model.share_dtransac_w_exporter = sum(eqm.X1+eqm.X0.*Share)./sum(eqm.X1+eqm.X0);
% 
% 

%% RETURN
    
    F = model;

end